Question

我在网上搜索了答案，但没有帮助（其他人遇到的所有问题都是由于语法或太旧的张量流版本）所以我决定问自己 - 我在这里。

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data

mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)

x = tf.placeholder(tf.float32, [None, 784])
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))
y = tf.nn.softmax(tf.matmul(x, W) + b)
y_ = tf.placeholder(tf.float32, [None, 10])

cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), 
reduction_indices=[1]))
train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)

sess = tf.InteractiveSession()

tf.global_variables_initializer().run()

for _ in range(1000):
  batch_xs, batch_ys = mnist.train.next_batch(100)
  sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})

correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
print(sess.run(accuracy, feed_dict={x: mnist.test.images,
                                    y_: mnist.test.labels}))

结果我收到了这个错误：

InvalidArgumentError: You must feed a value for placeholder tensor 
'Placeholder_6' with dtype float and shape [?,784]
 [[Node: Placeholder_6 = Placeholder[dtype=DT_FLOAT, shape=[?,784], 
_device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]

我的Tensorflow是1.4.0。并且整个代码似乎与教程中的代码完全相同。

Answer 1

似乎是某种变量冲突：在重新启动我的IDE之后，最终代码工作没有错误 - 我将此留给任何有同样麻烦的人。

Tensorflow MNIST教程代码错误

1 个答案: